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David Bullock

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Articles

Harvesting insights: interpretable machine learning to understand environmental drivers of U.S. maize and soybean yield

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By Harrison Smith Verified, Christopher Heffernan, Amanda J. Ashworth, L. Lanier Nalley, David Bullock, Jason Tullis, Phillip R. Owens
| Flipboard
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Harvesting insights: interpretable machine learning to understand environmental drivers of U.S. maize and soybean yield - Scientific Reports

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By Harrison Smith Verified, Christopher Heffernan, Amanda J. Ashworth, David Bullock, Phillip R. Owens, L. Lanier Nalley, Jason Tullis
| Nature Verified
Abstract Accurate crop yield prediction is crucial for enhancing food security and agricultural sustainability; however, existing models frequently struggle to capture the intricate relationships between environmental drivers and crop performance. Here we leveraged a large, spatially explicit yield monitor dataset of U.S. commercial maize (Zea mays) and soybean (Glycine max) fields (134 unique crop-site-years).
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Managing Rail Logistics Risks Faced by Upper Great Plains Grain Shippers: A Case Study Using Value‐at‐Risk

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By David Bullock, William Wilson, Isaac AsheSimon Wilson
| Wiley Online Library Verified
Conflicts of Interest The authors declare no conflicts of interest. References Addinsoft. 2024. “ XLSTAT Statistical and Data Analysis Solution.” (version 2024.3.0). Addinsoft. https://www.xlstat.com. , , , and . 2018. “Shipping Risk Management Practice Revisited: A New Portfolio Approach.” Transportation Research Part A: Policy and Practice 110: 274–290. , and . 2009. Shipping Derivatives and Risk Management. Palgrave Macmillan. , and . 2008.
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